ArticleISME communications2023
Exploring the competitive dynamic enzyme allocation scheme through enzyme cost minimization.
Article in ISME communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Improving Rice Root Development and Soil Health in Saline Soils: A Biochar and Microbial-Inoculated Biochar with Nitrogen Approach.Plants (Basel, Switzerland) · 2026Article
- Mycotransformation of anthracene by indigenous Trichoderma lixii and Talaromyces pinophilus isolates: insights into the metabolic pathways, enzyme profiles and acute toxicity.Biodegradation · 2025Article
- Effects of exogenous copper on microbial metabolic function and carbon use efficiency ofFrontiers in microbiology · 2024Article
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Authors and funding
4 authors.
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Abstract
Enzyme allocation (or synthesis) is a crucial microbial trait that mediates soil biogeochemical cycles and their responses to climate change. However, few microbial ecological models address this trait, particularly concerning multiple enzyme functional groups that regulate complex biogeochemical processes. Here, we aim to fill this gap by developing a COmpetitive Dynamic Enzyme ALlocation (CODEAL) scheme for six enzyme groups that act as indicators of inorganic nitrogen (N) transformations in the Microbial-ENzyme Decomposition (MEND) model. This allocation scheme employs time-variant allocation coefficients for each enzyme group, fostering mutual competition among the multiple groups. We show that the principle of enzyme cost minimization is achieved by using the substrate's saturation level as the factor for enzyme allocation, resulting in an enzyme-efficient pathway with minimal enzyme cost per unit metabolic flux. It suggests that the relative substrate availability affects the trade-off between enzyme production and metabolic flux. Our research has the potential to give insights into the nuanced dynamics of the N cycle and inspire the evolving landscape of enzyme-mediated biogeochemical processes in microbial ecological modeling, which is gaining increasing attention.
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